Top Tableau Scenario-Based Interview Questions Set -29 (1- 5)

 

1. How would you identify customers whose profit margin is higher than the company average?

Compare customer profit margin against overall company profit margin.

{ FIXED [Customer ID] :
SUM([Profit]) / SUM([Sales])
}
>
{ FIXED :
SUM([Profit]) / SUM([Sales])
}

This helps identify highly profitable customers.

---

2. How would you calculate the percentage of sales contributed by the Top 10 customers?

First identify Top 10 customers, then divide their sales by total sales.

IF RANK(SUM([Sales])) <= 10
THEN SUM([Sales])
END

Contribution %:

WINDOW_SUM(
IF RANK(SUM([Sales])) <= 10
THEN SUM([Sales])
END
)
/
WINDOW_SUM(SUM([Sales]))

---

3. How would you identify products whose current month sales are lower than last month?

Compare current month sales with previous month sales.

SUM([Sales])
<
LOOKUP(SUM([Sales]),-1)

Compute using Month.

This highlights declining products.

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4. How would you calculate customer tenure in days?

Calculate the number of days from first purchase until today.

DATEDIFF(
'day',
{ FIXED [Customer ID] :
MIN([Order Date])
},
TODAY()
)

This is commonly used in Customer Lifetime Value analysis.

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5. How would you identify regions where profit growth is negative?

Compare current period profit against previous period profit.

(
SUM([Profit])
-
LOOKUP(SUM([Profit]),-1)
)
/
ABS(LOOKUP(SUM([Profit]),-1))
< 0

This identifies regions experiencing profit decline.

Top Tableau Scenario-Based Interview Questions Set -28 (1- 7)

 

1. How would you identify the customer who contributed the highest profit in each region?

Use Rank on Profit and partition by Region.

RANK(SUM([Profit])) = 1

Compute Using: Customer Name
Partition By: Region

This returns the top profit-generating customer in every region.

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2. How would you calculate the average number of days taken to ship an order?

Calculate the difference between Order Date and Ship Date.

AVG(
DATEDIFF(
'day',
[Order Date],
[Ship Date]
))

This measures shipping efficiency.

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3. How would you identify products that have sales in every month of the year?

Count distinct sales months and compare with 12.

{ FIXED [Product Name] :
COUNTD(DATETRUNC('month',[Order Date]))
} = 12

This identifies consistently selling products.

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4. How would you calculate each customer's share of profit within their region?

Divide customer profit by total regional profit.

SUM([Profit])
/
WINDOW_SUM(SUM([Profit]))

Set Compute Using: Customer Name.

This shows profit contribution within a region.

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5. How would you identify orders where discount is given but profit is negative?

Filter orders having discount and loss.

[Discount] > 0
AND
[Profit] < 0

Useful for identifying poor discounting strategies.

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6. How would you calculate the average revenue generated per active month?

Divide total sales by distinct active months.

SUM([Sales])
/
COUNTD(
DATETRUNC('month',[Order Date])
)

This gives average monthly revenue.

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7. How would you identify customers whose latest purchase amount is higher than their average purchase amount?

Compare latest order sales with customer average sales.

IF [Order Date] =
{ FIXED [Customer ID] : MAX([Order Date]) }
THEN [Sales]
END

Compare it against:

{ FIXED [Customer ID] : AVG([Sales]) }

This identifies customers whose recent spending is above their historical average.